Forensic Face Sketch Recognition based on Pre-Selected Facial Regions

• 发表在: ICCSCE 2022 - Proceedings: 2022 12th IEEE International Conference on Control System, Computing and Engineering
• 主要作者: 2-s2.0-85142453639
• 格式: Conference paper
• 语言: English
• 出版: Institute of Electrical and Electronics Engineers Inc. 2022
• 在线阅读: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85142453639&doi=10.1109%2fICCSCE54767.2022.9935651&partnerID=40&md5=dd981b2d785758e9b28d21e24fa98787
• DOI: 10.1109/ICCSCE54767.2022.9935651

In law enforcement, face sketch recognition has been used to identify the criminal suspect. Usually, when there is no other evidence, a forensic artist will draw the face of the suspect based on the eyewitness description. Then, the forensic sketch will be matched with the mugshot images from the database in order to recognize and identify the potential suspect. However, the matching performance of the forensic sketches could be affected by various factors, and one of the major factors is the occlusion that exists in the sketch itself. This is because most of the suspects usually wear something that could help in hiding their identities, like a face mask, glasses, hoodie, or cap, when they are committing a crime. Since the mugshot images do not include the occlusion, it will make it harder to recognize the suspect in the matching process, even if the sketch and photo are from the same person. This is due to the larger Euclidean distance between the extracted features from these two images, particularly in the occlusion regions. Therefore, this study proposed a method that matches only the pre-selected regions that exclude occlusion in both images. This region of interest is pre-selected on the forensic face sketch before the same region is applied to all mugshot images. In this study, the forensic sketch with their corresponding photo was obtained from the PRIP-HDC dataset, and the Histogram of Gradient (HOG) was used for feature extraction. Based on the result obtained, this study's performance shows some improvement in recognizing the forensic sketches compared to the existing technique. © 2022 IEEE.